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On the Reuse Bias in Off-Policy Reinforcement Learning (IJCAI 2023)

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BIRIS

arXiv

This is the official implementation for On the Reuse Bias in Off-Policy Reinforcement Learning (Accepted in IJCAI 2023).

Usage

Gym-MiniGrid

The code for MiniGrid is in the fold MiniGrid, thus you can train the code by

cd MiniGrid
conda create -n BIRIS-minigrid python=3.8
conda activate BIRIS-minigrid
pip install -r requirements.txt
python main.py --sample_algorithm IS --use_biris True --buffer_size 40 --env MiniGrid-Empty-5x5-v0

You can choose sample_algorithm=IS or WIS, use_biris=True or False, buffer_size=30, 40, or 50, env=MiniGrid-Empty-5x5-v0, MiniGrid-Empty-Random-5x5-v0, MiniGrid-Empty-6x6-v0, MiniGrid-Empty-Random-6x6-v0, MiniGrid-Empty-8x8-v0, or MiniGrid-Empty-16x16-v0, to reproduce the results in the paper.

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On the Reuse Bias in Off-Policy Reinforcement Learning (IJCAI 2023)

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